Sökning: "random game"

Visar resultat 1 - 5 av 33 uppsatser innehållade orden random game.

  1. 1. Customer Churn Prediction for PC Games : Probability of churn predicted for big-spenders usingsupervised machine learning

    Master-uppsats, KTH/Optimeringslära och systemteori

    Författare :Valgerdur Tryggvadottir; [2019]
    Nyckelord :Customer churn prediction; whales; data analysis; machine learning; binary classification.; Kund churn prediktering; valar; dataanalys; maskinlärning; binär klas-sificering.;

    Sammanfattning : Paradox Interactive is a Swedish video game developer and publisher which has players all around the world. Paradox’s largest platform in terms of amount of players and revenue is the PC. LÄS MER

  2. 2. DQN Tackling the Game of Candy Crush Friends Saga : A Reinforcement Learning Approach

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Alice Karnsund; [2019]
    Nyckelord :;

    Sammanfattning : This degree project presents a reinforcement learning (RL) approach called deep Q-network (DQN) for learning how to play the game Candy Crush Friends Saga (CCFS). The DQN algorithm is implemented together with three extensions, which in 2015 resulted in a new state-of-the-art on the Atari 2600 domain. LÄS MER

  3. 3. Using Reinforcement Learning for Games with Nondeterministic State Transitions

    Master-uppsats, Linköpings universitet/Statistik och maskininlärning

    Författare :Max Fischer; [2019]
    Nyckelord :reinforcement learning; proximal policy optimization; PPO; machine learning; artificial intelligence; deep learning; neural network; candy crush; mobile game;

    Sammanfattning : Given the recent advances within a subfield of machine learning called reinforcement learning, several papers have shown that it is possible to create self-learning digital agents, agents that take actions and pursue strategies in complex environments without any prior knowledge. This thesis investigates the performance of the state-of-the-art reinforcement learning algorithm proximal policy optimization, when trained on a task with nondeterministic state transitions. LÄS MER

  4. 4. Test case prioritization in the context of a video game development project

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Rami Karim; [2019]
    Nyckelord :;

    Sammanfattning : Regression testing is an important part of software development and is integral for finding regression errors caused by code changes or issues with revision control. However, executing all test cases in the test suite is often infeasible. One solution to this problem is to use a prioritization technique. LÄS MER

  5. 5. Increasingly Complex Environments in Deep Reinforcement Learning

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS); KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Oskar Eriksson; Mattias Larsson; [2019]
    Nyckelord :;

    Sammanfattning : In this thesis, we used deep reinforcement learning to train autonomous agents and evaluated the impact of increasing the complexity of the training environment over time. This was compared to using a fixed complexity. LÄS MER